#1
 
 
Difference between Problem Solving & Dynamic Programming
Hello sir I want to know about Difference between Problem Solving & Dynamic Programming so please give me its details.

#2
 
 
Re: Difference between Problem Solving & Dynamic Programming
Dynamic programming is a useful mathematical technique for making a sequence of interrelated decisions. It provides a systematic procedure for determining the optimal combination of decisions. In contrast to linear programming, there does not exist a standard mathematical formulation of “the” dynamic programming problem. Rather, dynamic programming is a general type of approach to problem solving, and the particular equations used must be developed to fit each situation. Therefore, a certain degree of ingenuity and insight into the general structure of dynamic programming problems is required to recognize when and how a problem can be solved by dynamic programming procedures. These abilities can best be developed by an exposure to a wide variety of dynamic programming applications and a study of the characteristics that are common to all these situations. A large number of illustrative examples are presented for this purpose. For the rest of the details you can download the pdf file provided.
__________________ Answered By StudyChaCha Member 
#4
 
 
Re: Difference between Problem Solving & Dynamic Programming
Dynamic Programming (DP) is an algorithmic technique for solving an optimization problem by breaking it down into simpler subproblems and utilizing the fact that the optimal solution to the overall problem depends upon the optimal solution to its subproblem. The greedy method computes its solution by making its choices in a serial forward fashion, never looking back or revising previous choices About Dynamic programming: Dynamic programming is mainly an optimization over plain recursion. Dynamic Programming is generally slower. For example, Bellman Ford algorithm takes O(VE) time. Dynamic programming computes its solution bottom up or top down by synthesizing them from smaller optimal sub solutions. Please find the below attached file for the details about Dynamic programming: Dynamic programming details Some topics you will study: Knapsack. LCS. Matrix Chain Multipication . Coin Change. LIS. Edit Distance. Balanced Partition. Optimal Strategy for a Game. List of some books to prepare: Learning PHP, MySQL & JavaScript With jQuery, CSS & HTML5 Robin Nixon Algorithms Illuminated Greedy Algorithms and Dynamic Programming Tim Roughgarden Dynamic Programming and Optimal Control, Vol. I, 4th Edition Dimitri Bertsekas Dynamic Programming and Optimal Control Dimitri P. Bertsekas 